A5014580516- Scientific Computing and Data Management
- Privacy-Preserving Technologies in Data
- Research Data Management Practices
- Biomedical and Engineering Education
- Quality and Safety in Healthcare
- Data Quality and Management
- Artificial Intelligence in Healthcare
- Medical Coding and Health Information
- Electronic Health Records Systems
- Blockchain Technology Applications and Security
- Biosensors and Analytical Detection
RWTH Aachen University
2021-2024
In recent years, data-driven medicine has gained increasing importance in terms of diagnosis, treatment, and research due to the exponential growth health care data. However, data protection regulations prohibit centralisation for analysis purposes because potential privacy risks like accidental disclosure third parties. Therefore, alternative usage policies, which comply with present guidelines, are particular interest.We aim enable analyses on sensitive patient by simultaneously complying...
The development of platforms for distributed analytics has been driven by a growing need to comply with various governance-related or legal constraints. Among these platforms, the so-called Personal Health Train (PHT) is one representative that emerged over recent years. However, in projects require data from sites featuring different PHT infrastructures, institutions are facing challenges emerging combination multiple ecosystems, including governance, regulatory compliance, modification...
The constant upward movement of data-driven medicine as a valuable option to enhance daily clinical practice has brought new challenges for data analysts get access but sensitive due privacy considerations. One solution most these are Distributed Analytics (DA) infrastructures, which technologies fostering collaborations between healthcare institutions by establishing privacy-preserving network sharing. However, in order participate such network, lot technical and administrative...
In recent years, implementations enabling Distributed Analytics (DA) have gained considerable attention due to their ability perform complex analysis tasks on decentralised data by bringing the data. These concepts propose privacy-enhancing alternatives centralisation approaches, which restricted applicability in case of sensitive ethical, legal or social aspects. Nevertheless, immanent problem DA-enabling architectures is black-box-alike behaviour highly distributed components originating...
With the introduction of data protection regulations, need for innovative privacy-preserving approaches to process and analyse sensitive has become apparent. One approach is Personal Health Train (PHT) that brings analysis code conducts processing at premises. However, despite its demonstrated success in various studies, execution external environments, such as hospitals, introduces new research challenges because interactions with are often incomprehensible lack transparency. These raise...